UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) UvA-DARE (Digital Academic Repository) Statistical advances in clinical neuropsychology Agelink van Rentergem Zandvliet, J.A. Publication date 2018 Document Version Other version License Other Link to publication Citation for published version (APA): Agelink van Rentergem Zandvliet, J. A. (2018). Statistical advances in clinical neuropsychology. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Download date:01 Sep 2021
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UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl)
Citation for published version (APA):Agelink van Rentergem Zandvliet, J. A. (2018). Statistical advances in clinicalneuropsychology.
General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s)and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an opencontent license (like Creative Commons).
Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, pleaselet the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the materialinaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letterto: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. Youwill be contacted as soon as possible.
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9APPENDICES ACCOMPANY ING CHAPTER 5 :COGNIT IVE DOMAINS IN NEUROPSYCHOLOGY:SUPPORT FOR THE CATTELL -HORN-CARROLLMODEL IN TWO RESEARCH SYNTHESES
9.1 search terms used in psycinfo
#1 Factor model
factor analysis/ OR factor structure/ OR structural equation model-ing/ OR (factor* model* OR factor* analy* OR structural equation*model* OR EFA OR CFA OR SEM OR factor* structur* OR confirma-tory factor* OR exploratory factor*).ti,ab,id.
#2 Specific neuropsychological tests
stroop color word test/ OR stroop effect/ ORwechsler memory scale/OR wisconsin card sorting test/ OR verbal learn*.tm. OR ((clock*AND (test* OR draw*)) OR (tower AND (test* OR london OR hanoi))OR benton OR vis* retent* OR BVRT OR fac* recogni* OR BFRT ORjudg* of line* OR line orientation OR JLO OR BJLO OR JOLO ORblock design OR blockdesign OR Kohs OR boston naming OR BNTOR brixton OR spatial anticipation OR BSAT OR card sort* task* ORcard sort* test* OR cardsort* test* OR WCST OR MWCST OR com-plex figur* OR rcf* OR rocf* OR rey-osterrieth OR digit* span* ORdigitspan OR (span* ADJ1 (forward* OR back*)) OR spanforwardOR digit* symbol* OR symbol* substitution* OR symbol coding ORDSST* OR family pictures OR figur* fluency OR groov* peg* OR pur-due peg* OR pegboard OR letter fluency OR cowat OR controlledoral word association OR controlled word association OR controlledassociation* OR letter number OR LNS OR location learning OR LLTOR logical memory OR matr* reas* OR object* assemb* OR pac* au-dit* seri* additi* OR PASAT OR pict* arrangement* OR pict* compl*OR rivermead behavio* OR rbmt* OR selecti* remindi* OR srt ORBuschke OR VSRT OR semantic fluency OR verbal fluency OR cate-gory fluency OR animal* naming OR occupation* naming OR spatialspan OR stroop OR symbol* search* OR trail making OR trial mak-ing OR tmt OR halstead reitan OR verbal learn* test* OR verbal learn*task* OR RAVLT* OR AVLT* OR CVLT* OR HVLT* OR verbal pair*associat* OR visual reproduction OR WMS*).ti,ab,id,tm.
#3 Clinical neuropsychological test batteries
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140 appendices accompanying chapter 5
(test battery/ OR (((tests OR test scores OR test results) ADJ2 (at-tention* OR cognit* OR memory OR neuropsych* OR visual OR visu-ospatial* OR visuomotor OR verbal* OR executive OR learning OR IQOR motor OR auditory OR perception OR inhibit* OR psychometr*))OR (test* AND battery)).ti,ab,id,tm.) AND (neuropsychol*).ti,ab,id,hw,jx.
1 AND (2 OR 3)
9.2 test variables of interest.
Trail Making Test A, Trail Making Test B, Stroop Color, Stroop Word,Stroop Color-Word, Letter Fluency / FAS / COWAT, Semantic Flu-ency / Category Fluency / Animal Naming, Verbal Learning TestTotal, Verbal Learning Test Recall, Verbal Learning Test Recognition,WAIS Vocabulary, WAIS Similarities, WAIS Information, WAIS Arith-metic, WAIS Letter Number Sequencing, WAIS Comprehension, WAISPicture Completion, WAIS Block Design, WAIS Matrix Reasoning,WAIS Digit Symbol Substitution / Coding, WAIS Symbol Search,WAIS Picture Arrangement, WAIS Object Assembly, Logical Memory/ Story Immediate, Logical Memory / Story Delayed, WMS FacesImmediate, WMS Faces Delayed, WMS Verbal Paired Associates Im-mediate, WMS Verbal Paired Associates Delayed, WMS Visual PairedAssociates, WMS Family Pictures Immediate, WMS Family PicturesDelayed, WMS Visual Reproduction, WMS Spatial Span, Digit SpanForward, Digit Span Backward, Rey Complex Figure Copy, Rey Com-plex Figure Immediate Recall, Rey Complex Figure Delayed Recall,Raven Progressive Matrices, Wisconsin Number of Categories, Wis-consin Number of Perseverative Errors, Wisconsin Number of Perse-verative Responses, Token Test Score, Grooved Pegboard Dominant,Grooved Pegboard Non-dominant, Benton Visual Retention Test, Brix-ton Spatial Anticipation, Rivermead Immediate 1 + 2, Rivermead De-layed 1 + 2, Clock Drawing Test, Boston Naming Test, Ruff FiguralFluency Test, Ruff 2 and 7, Buschke Selective Reminding Test TotalRecall (TR), Buschke Selective Reminding Test Long Term Retrieval(LTR), Buschke Selective Reminding Test Long Term Storage (LTS),Buschke Selective Reminding Test Consistent Long Term Retrieval(CLTR), Free and Cued Selective Reminding Test (FCSRT), BuschkeSelective Reminding Test Delayed Recall (DR), Benton Facial Recog-nition Test, Symbol Digit Modalities Test, Brief Visuospatial MemoryTest, Judgement of Line Orientation, Tower of London Total numberof moves, Continuous Performance Test (d’), Peabody Picture Vocab-ulary Test, PASAT Total number correct, BADS Zoo map, BADS Keysearch
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9.3 analysis without tmt b from royall et al . (2015) 141
Figure 9.1: Bivariate raw and partial correlations between Trail Making Test B and LetterFluency, plotted for different studies. The studies are ordered by the size ofthe correlation.
9.3 analysis without tmt b from royall et al . (2015)
Figure 1, left hand panel, shows that one correlation between TMTBand LF is exceptional, in that is positive and large. This is also thecase for the correlation between TMTB and LMII from this study inFigure 2, so it is not LF that is at fault. These findings remain afterpartialing out the effect of age, sex, and level of education (right handpanel). This could be a case of a coding error, but Royall et al. (2015)is clear that the TMTB variable refers to the score in seconds, likeother studies. Royall et al. (2015) also note that the correlations withTMTB seem strange. One last option is that it is simply due to sam-pling variance. However, given that this concerns an impressive 875participants, this is unlikely. Other correlations that seemed differentfrom the rest came from much smaller studies.
All correlations with TMTB were removed from the Royall correla-tion matrix for the main analysis, leaving LMII, BNT and LF. We didhowever run the analysis with these correlations with TMTB included.The results are given in Table 1. The conclusions do not differ fromthe conclusions of the main analysis: The second Jewsbury model wasconsidered best in this analysis as well.
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142 appendices accompanying chapter 5
Figure 9.2: Bivariate raw and partial correlations between Trail Making Test B and Log-ical Memory II, plotted for different studies. The studies are ordered by thesize of the correlation.
Table 9.1: Comparison Results with Correlations with TMT B from Royall etal. (2015) Included.
χ2(df) RMSEA SRMR CFI AIC BIC
One factor 11193.5 (54) 0.058 0.218 0.937 11085.5 10599
Jewsbury 2 1307.2 (41) 0.023 0.059 0.993 1225.2 855.9*Model did not converge.
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9.4 study characteristics and correlation matrices 143
9.4 study characteristics and correlation matrices
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144 appendices accompanying chapter 5
Table 9.2: Adrover-Roig, D., Sesé, A., Barceló, F., & Palmer, A. (2012). A latent variableapproach to executive control in healthy ageing. Brain and Cognition, 78(3),284-299. doi:10.1016/j.bandc.2012.01.005
N = 122
Sex coding: male > female
Education coding: higher is better
Correlation matrix available from original publication
Table 9.3: Albert, M., Massaro, J., DeCarli, C., Beiser, A., Seshadri, S., Wolf, P. A., &Au, R. (2010). Profiles by sex of brain MRI and cognitive function in theframingham offspring study. Alzheimer Disease and Associated Disorders, 24(2),190-193. doi:10.1097/WAD.0b013e3181c1ed44
N = 2085
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB LMI LMII
AGE 1 -0.011 -0.218 0.311 0.398 -0.21 -0.227
SEX -0.011 1 -0.096 -0.075 -0.038 0.11 0.12
EDU -0.218 -0.096 1 -0.155 -0.286 0.311 0.307
TMTA 0.311 -0.075 -0.155 1 0.57 -0.206 -0.211
TMTB 0.398 -0.038 -0.286 0.57 1 -0.281 -0.299
LMI -0.21 0.11 0.311 -0.206 -0.281 1 0.86
LMII -0.227 0.12 0.307 -0.211 -0.299 0.86 1
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9.4 study characteristics and correlation matrices 145
Table 9.4: Andrejeva, N., Knebel, M., Dos Santos, V., Schmidt, J., Herold, C. J., Tudoran,R., ... & Gorenc-Mahmutaj, L. (2016). Neurocognitive deficits and effects of cog-nitive reserve in mild cognitive impairment. Dementia and Geriatric CognitiveDisorders, 41(3-4), 199-209. doi:10.1159/000443791
N = 65
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB LMI LMII SF BNT VLT-TR VLT-DR
Table 9.5: Andreotti, C., & Hawkins, K. A. (2015). RBANS norms based on the relation-ship of age, gender, education, and WRAT-3 reading to performance within anolder African American sample. The Clinical Neuropsychologist, 29(4), 442-465.doi:10.1080/13854046.2015.1039589
N = 289
Sex coding: Sex not included
Education coding: higher is better
Correlation matrix available from original publication
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146 appendices accompanying chapter 5
Table 9.6: Barnes, L. L., Yumoto, F., Capuano, A., Wilson, R. S., Bennett, D. A., & Tractenberg, R. E. (2016). Ex-amination of the factor structure of a global cognitive function battery across race and time. Jour-nal of the International Neuropsychological Society, 22(1), 66-75. doi:10.1017/S1355617715001113
N = 2854
Sex coding: male > female
Education coding: higher is better
AGE SEX EDU LMI LMII SF DSF DSB COD BNT VLT-TR VLT-DR
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9.4 study characteristics and correlation matrices 147
Table 9.7: Bennett, I. J., & Stark, C. E. (2016). Mnemonic discrimination relates to perforant path in-tegrity: an ultra-high resolution diffusion tensor imaging study. Neurobiology of Learningand Memory, 129, 107-112. doi:10.1016/j.nlm.2015.06.014
N = 109
Sex coding: male > female
Education coding: higher is better
AGE SEX EDU TMTA TMTB LMI LMII LF SF DSF DSB VLT-TR VLT-DR
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148 appendices accompanying chapter 5
Table 9.8: Bezdicek, O., Libon, D. J., Stepankova, H., Panenkova, E.,Lukavsky, J., Garrett, K. D., ... & Kopecek, M. (2014). Develop-ment, validity, and normative data study for the 12-word Philadel-phia Verbal Learning Test [czP (r) VLT-12] among older and veryold Czech adults. The Clinical Neuropsychologist, 28(7), 1162-1181.doi:10.1080/13854046.2014.952666
Table 9.9: Booth, T., Royle, N. A., Corley, J., Gow, A. J., Hernández,M. D. C. V., Maniega, S. M., ... & Deary, I. J. (2015). As-sociation of allostatic load with brain structure and cogni-tive ability in later life. Neurobiology of Aging, 36(3), 1390-1399.doi:10.1016/j.neurobiolaging.2014.12.020
N = 970
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU LMI LMII SF DSB COD
AGE 1 0.02 -0.071 -0.18 -0.169 -0.144 -0.141 -0.198
SEX 0.02 1 -0.029 0.077 0.108 0.059 -0.041 0.162
EDU -0.071 -0.029 1 0.307 0.287 0.241 0.199 0.285
LMI -0.18 0.077 0.307 1 0.873 0.197 0.238 0.238
LMII -0.169 0.108 0.287 0.873 1 0.195 0.23 0.244
SF -0.144 0.059 0.241 0.197 0.195 1 0.28 0.342
DSB -0.141 -0.041 0.199 0.238 0.23 0.28 1 0.264
COD -0.198 0.162 0.285 0.238 0.244 0.342 0.264 1
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9.4 study characteristics and correlation matrices 149
Table 9.10: Bouazzaoui, B., Fay, S., Taconnat, L., Angel, L., Vanneste, S., & Isingrini,M. (2013). Differential involvement of knowledge representation and ex-ecutive control in episodic memory performance in young and olderadults. Canadian Journal of Experimental Psychology/Revue Canadienne dePsychologie Expérimentale, 67(2), 100-107. doi:10.1037/a0028517
N = 120
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU LF SF
AGE 1 0.093 -0.229 -0.324 -0.23
SEX 0.093 1 -0.099 -0.189 -0.067
EDU -0.229 -0.099 1 0.312 0.038
LF -0.324 -0.189 0.312 1 0.411
SF -0.23 -0.067 0.038 0.411 1
Table 9.11: Bowden, S. C., Cook, M. J., Bardenhagen, F. J., Shores, E. A., & Carstairs, J.R. (2004). Measurement invariance of core cognitive abilities in heteroge-neous neurological and community samples. Intelligence, 32(4), 363-389.doi:10.1016/j.intell.2004.05.002
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150 appendices accompanying chapter 5
Table 9.12: Bunce, D., Batterham, P. J., Christensen, H., & Mackinnon, A. J. (2014).Causal associations between depression symptoms and cognition in acommunity-based cohort of older adults. The American Journal of GeriatricPsychiatry, 22(12), 1583-1591. doi:10.1016/j.jagp.2014.01.004
N = 853
Sex coding: male > female
Education coding: higher is better
AGE 1 -0.07 -0.07 -0.24 -0.33
SEX -0.07 1 0.17 0.07 0.02
EDU -0.07 0.17 1 0.16 0.34
SF -0.24 0.07 0.16 1 0.47
COD -0.33 0.02 0.34 0.47 1
Table 9.13: Chan, R. C., Wang, Y., Wang, L., Chen, E. Y., Manschreck, T. C., Li, Z. J.,... & Gong, Q. Y. (2009). Neurological soft signs and their relationships toneurocognitive functions: A re-visit with the structural equation model-ing design. PLoS One, 4(12), 1-8. doi:10.1371/journal.pone.0008469
N = 160
Sex coding: male > female
Education coding: higher is better
Table 9.14: Chen, Y. C., Jung, C. C., Chen, J. H., Chiou, J. M., Chen, T. F., Chen, Y.F., ... & Lee, M. S. (2017). Association of dietary patterns with globaland domain-specific cognitive decline in Chinese elderly. Journal of theAmerican Geriatrics Society, 65(6), 1159-1167. doi:10.1111/jgs.14741
N = 475
Sex coding: male > female
Education coding: higher is better
AGE SEX EDU TMTA TMTB LMI LMII SF DSB
AGE 1 0.238 -0.089 0.376 0.424 -0.336 -0.301 -0.349 -0.257
SEX 0.238 1 0.287 -0.038 0.007 -0.027 -0.023 -0.36 -0.036
EDU -0.089 0.287 1 -0.373 -0.25 0.302 0.324 -0.017 0.289
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9.4 study characteristics and correlation matrices 151
Table 9.15: Ciccarelli, N., Fabbiani, M., Baldonero, E., Fanti, I., Cauda, R., Gi-ambenedetto, S. D., & Silveri, M. C. (2012). Effect of aging and hu-man immunodeficiency virus infection on cognitive abilities. Journalof the American Geriatrics Society, 60(11), 2048-2055. doi:10.1111/j.1532-5415.2012.04213.x
Table 9.16: Darst, B. F., Koscik, R. L., Hermann, B. P., La Rue, A., Sager, M. A.,Johnson, S. C., & Engelman, C. D. (2015). Heritability of cognitive traitsamong siblings with a parental history of Alzheimer’s disease. Journal ofAlzheimer’s Disease, 45(4), 1149-1155. doi:10.3233/JAD-142658
N = 1226
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB LMI LMII DSF DSB VLT-TR VLT-DR
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152 appendices accompanying chapter 5
Table 9.17: Duff, K. D., Langbehn, D. R., Schoenberg, M. R., Moser, D. J., Baade, L. E., Mold, J. W.,. . . Adams, R. L. (2006). Examining the repeatable battery for the assessment of neu-ropsychological status: Factor analytic studies in an elderly sample. The American Journalof Geriatric Psychiatry, 14, 976-979. doi:10.1097/01.JGP.0000229690.70011
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9.4 study characteristics and correlation matrices 153
Table 9.19: Fernaeus, S. E., Östberg, P., Wahlund, L. O., & Hellström, Å.(2014). Memory factors in Rey AVLT: implications for early stag-ing of cognitive decline. Scandinavian Journal of Psychology, 55(6),546-553. doi:10.1111/sjop.12157
N = 42
Sex coding: male > female
Education coding: higher is better
AGE SEX EDU TMTA LMI LMII DSF DSB VLT-TR
AGE 1 -0.011 -0.407 -0.028 -0.239 -0.443 -0.241 -0.161 -0.367
SEX -0.011 1 -0.286 0.222 -0.111 -0.282 0.154 0.151 -0.217
EDU -0.407 -0.286 1 -0.264 0.3 0.187 0.058 0.088 0.476
Table 9.20: Ferreira, N. V., Cunha, P. J., da Costa, D. I., dos Santos, F., Costa,F. O., Consolim-Colombo, F., & Irigoyen, M. C. (2015). Associ-ation between functional performance and executive cognitivefunctions in an elderly population including patients with lowankle–brachial index. Clinical Interventions in Aging, 10, 839-847.doi:10.2147/CIA.S69270
N = 40
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU LF SF DSF DSB
AGE 1 -0.264 0.213 -0.054 -0.066 0.058 -0.266
SEX -0.264 1 -0.139 0.152 0.287 0.262 0.356
EDU 0.213 -0.139 1 0.243 0.28 0.177 -0.024
LF -0.054 0.152 0.243 1 0.539 0.24 0.48
SF -0.066 0.287 0.28 0.539 1 0.42 0.501
DSF 0.058 0.262 0.177 0.24 0.42 1 0.508
DSB -0.266 0.356 -0.024 0.48 0.501 0.508 1
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154 appendices accompanying chapter 5
Table 9.21: Fortin, A., & Caza, N. (2014). A validation study of memory andexecutive functions indexes in French-speaking healthy young andolder adults. Canadian Journal on Aging/La Revue canadienne du vieillisse-ment, 33(1), 60-71. doi:10.1017/S0714980813000445
N = 98
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU LMI LF DSB VLT-DR
AGE 1 0.027 0.005 -0.408 0.11 -0.382 -0.315
SEX 0.027 1 -0.234 0.062 -0.026 -0.006 0.344
EDU 0.005 -0.234 1 0.045 0.279 0.074 0.072
LMI -0.408 0.062 0.045 1 -0.114 0.16 0.4
LF 0.11 -0.026 0.279 -0.114 1 0.13 0.117
DSB -0.382 -0.006 0.074 0.16 0.13 1 0.253
VLT-DR -0.315 0.344 0.072 0.4 0.117 0.253 1
Table 9.22: Gallagher, P., Gray, J. M., Watson, S., Young, A. H., & Ferrier,I. N. (2014). Neurocognitive functioning in bipolar depression: acomponent structure analysis. Psychological Medicine, 44(5), 961-974.doi:10.1017/S0033291713001487
N = 47
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU LF DSF DSB COD VLT-TR VLT-DR
AGE 1 0.261 -0.097 0.196 -0.102 -0.025 -0.191 -0.442 -0.359
SEX 0.261 1 -0.046 0.196 0.037 -0.056 0.383 -0.007 -0.1
EDU -0.097 -0.046 1 0.127 0.029 0.383 0.397 0.247 0.15
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9.4 study characteristics and correlation matrices 155
Table 9.23: Horvat, P., Richards, M., Malyutina, S., Pajak, A., Kubinova, R.,Tamosiunas, A., ... & Bobak, M. (2014). Life course socioeco-nomic position and mid-late life cognitive function in EasternEurope. Journals of Gerontology Series B: Psychological Sciences andSocial Sciences, 69(3), 470-481. doi:10.1093/geronb/gbu014
Country: Czech Republic
N = 5490
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU SF VLT-TR
AGE 1 -0.08 -0.09 -0.21 -0.26
SEX -0.08 1 -0.32 0.01 0.27
EDU -0.09 -0.32 1 0.3 0.3
SF -0.21 0.01 0.3 1 0.4
VLT-TR -0.26 0.27 0.3 0.4 1
Table 9.24: Horvat, P., Richards, M., Malyutina, S., Pajak, A., Kubinova, R.,Tamosiunas, A., ... & Bobak, M. (2014). Life course socioeco-nomic position and mid-late life cognitive function in EasternEurope. Journals of Gerontology Series B: Psychological Sciences andSocial Sciences, 69(3), 470-481. doi:10.1093/geronb/gbu014
Country: Lithuania
N = 6762
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU SF VLT-TR
AGE 1 -0.02 -0.21 -0.29 -0.37
SEX -0.02 1 -0.01 -0.01 0.28
EDU -0.21 -0.01 1 0.4 0.43
SF -0.29 -0.01 0.4 1 0.4
VLT-TR -0.37 0.28 0.43 0.4 1
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 164PDF page: 164PDF page: 164PDF page: 164
156 appendices accompanying chapter 5
Table 9.25: Horvat, P., Richards, M., Malyutina, S., Pajak, A., Kubinova, R.,Tamosiunas, A., ... & Bobak, M. (2014). Life course socioeco-nomic position and mid-late life cognitive function in EasternEurope. Journals of Gerontology Series B: Psychological Sciences andSocial Sciences, 69(3), 470-481. doi:10.1093/geronb/gbu014
Country: Poland
N = 10317
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU SF VLT-TR
AGE 1 -0.05 -0.11 -0.29 -0.36
SEX -0.05 1 -0.09 0 0.16
EDU -0.11 -0.09 1 0.38 0.36
SF -0.29 0 0.38 1 0.55
VLT-TR -0.36 0.16 0.36 0.55 1
Table 9.26: Horvat, P., Richards, M., Malyutina, S., Pajak, A., Kubinova, R.,Tamosiunas, A., ... & Bobak, M. (2014). Life course socioeco-nomic position and mid-late life cognitive function in EasternEurope. Journals of Gerontology Series B: Psychological Sciences andSocial Sciences, 69(3), 470-481. doi:10.1093/geronb/gbu014
Country: Russia
N = 8277
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU SF VLT-TR
AGE 1 -0.02 -0.17 -0.38 -0.42
SEX -0.02 1 -0.04 -0.03 0.17
EDU -0.17 -0.04 1 0.28 0.29
SF -0.38 -0.03 0.28 1 0.47
VLT-TR -0.42 0.17 0.29 0.47 1
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 165PDF page: 165PDF page: 165PDF page: 165
9.4 study characteristics and correlation matrices 157
Table 9.27: Hedden, T., & Yoon, C. (2006). Individual differences in executiveprocessing predict susceptibility to interference in verbal work-ing memory. Neuropsychology, 20(5), 511-528. doi:10.1037/0894-4105.20.5.511.supp.
N = 121
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB DSB
AGE 1 -0.16 0.14 0.34 0.34 -0.19
SEX -0.16 1 -0.21 -0.07 0.01 -0.07
EDU 0.14 -0.21 1 0.05 -0.11 0.25
TMTA 0.34 -0.07 0.05 1 0.57 -0.23
TMTB 0.34 0.01 -0.11 0.57 1 -0.39
DSB -0.19 -0.07 0.25 -0.23 -0.39 1
Table 9.28: Hedden, T., Mormino, E. C., Amariglio, R. E., Younger, A. P.,Schultz, A. P., Becker, J. A., ... & Rentz, D. M. (2012). Cognitiveprofile of amyloid burden and white matter hyperintensities incognitively normal older adults. Journal of Neuroscience, 32(46),16233-16242. doi:10.1523/JNEUROSCI.2462-12.2012
N = 168
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB LF SF DSB COD
AGE 1 -0.04 -0.05 0.12 0.22 0.01 -0.19 -0.03 -0.22
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 166PDF page: 166PDF page: 166PDF page: 166
158 appendices accompanying chapter 5
Table 9.29: Hueng, T. T., Lee, I. H., Guog, Y. J., Chen, K. C., Chen, S. S.,Chuang, S. P., ... & Yang, Y. K. (2011). Is a patient-administereddepression rating scale valid for detecting cognitive deficits inpatients with major depressive disorder? Psychiatry and ClinicalNeurosciences, 65(1), 70-76. doi:10.1111/j.1440-1819.2010.02166.x
N = 40
Sex coding: male > female
Education coding: higher is better
AGE SEX EDU LMI LMII
AGE 1 0.039 -0.552 -0.315 -0.279
SEX 0.039 1 0.068 -0.143 -0.13
EDU -0.552 0.068 1 0.578 0.489
LMI -0.315 -0.143 0.578 1 0.896
LMII -0.279 -0.13 0.489 0.896 1
Table 9.30: Karagiannopoulou, L., Karamaouna, P., Zouraraki, C., Rous-sos, P., Bitsios, P., & Giakoumaki, S. G. (2016). Cogni-tive profiles of schizotypal dimensions in a community co-hort: Common properties of differential manifestations. Jour-nal of Clinical and Experimental Neuropsychology, 38(9), 1050-1063.doi:10.1080/13803395.2016.1188890
N = 200
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB LF SF
AGE 1 0.015 0.3 0.022 0.077 0.151 0.126
SEX 0.015 1 0.264 0.042 0.009 0.218 0.091
EDU 0.3 0.264 1 -0.28 -0.314 0.415 0.409
TMTA 0.022 0.042 -0.28 1 0.582 -0.239 -0.19
TMTB 0.077 0.009 -0.314 0.582 1 -0.187 -0.207
LF 0.151 0.218 0.415 -0.239 -0.187 1 0.491
SF 0.126 0.091 0.409 -0.19 -0.207 0.491 1
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 167PDF page: 167PDF page: 167PDF page: 167
9.4 study characteristics and correlation matrices 159
Table 9.31: Kesse-Guyot, E., Andreeva, V. A., Lassale, C., Hercberg, S., &Galan, P. (2014). Clustering of midlife lifestyle behaviors and sub-sequent cognitive function: a longitudinal study. American Journalof Public Health, 104(11), 170-177. doi:10.2105/AJPH.2014.302121
N = 2470
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB LF SF DSF DSB
AGE 1 -0.11 -0.1 0.25 0.24 -0.08 -0.16 -0.09 -0.06
Table 9.32: Kim, J., Jeong, J. H., Han, S. H., Ryu, H. J., Lee, J. Y., Ryu,S. H., ... & Choi, S. H. (2013). Reliability and validity ofthe short form of the literacy-independent cognitive assess-ment in the elderly. Journal of Clinical Neurology, 9(2), 111-117.doi:10.3988/jcn.2013.9.2.111
N = 639
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU SF VLT-TR VLT-DR
AGE 1 -0.01 -0.255 -0.256 -0.337 -0.317
SEX -0.01 1 -0.409 -0.216 0.182 0.25
EDU -0.255 -0.409 1 0.37 0.2 0.049
SF -0.256 -0.216 0.37 1 0.263 0.258
VLT-TR -0.337 0.182 0.2 0.263 1 0.642
VLT-DR -0.317 0.25 0.049 0.258 0.642 1
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 168PDF page: 168PDF page: 168PDF page: 168
160 appendices accompanying chapter 5
Table 9.33: Komulainen, P., Pedersen, M., Hänninen, T., Bruunsgaard, H., Lakka, T. A., Kivipelto,M., ... & Rauramaa, R. (2008). BDNF is a novel marker of cognitive function in age-ing women: the DR’s EXTRA Study. Neurobiology of Learning and Memory, 90(4), 596-603.doi:10.1016/j.nlm.2008.07.014
N = 1388
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU SF BNT VLT-TR VLT-DR
AGE 1 0.028 -0.194 -0.189 -0.208 -0.265 -0.24
SEX 0.028 1 0.026 -0.01 -0.23 0.219 0.168
EDU -0.194 0.026 1 0.267 0.347 0.358 0.291
SF -0.189 -0.01 0.267 1 0.375 0.401 0.343
BNT -0.208 -0.23 0.347 0.375 1 0.253 0.238
VLT-TR -0.265 0.219 0.358 0.401 0.253 1 0.746
VLT-DR -0.24 0.168 0.291 0.343 0.238 0.746 1
Table 9.34: Krueger, K. R., Wilson, R. S., Bennett, D. A., & Aggarwal, N. T. (2009). A battery of tests forassessing cognitive function in older Latino persons. Alzheimer Disease and Associated Disor-ders, 23(4), 384. doi:10.1097/WAD.0b013e31819e0bfc
N = 66
Sex coding: male > female
Education coding: higher is better
AGE SEX EDU LMI LMII SF DSF DSB COD BNT VLT-TR VLT-DR
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 169PDF page: 169PDF page: 169PDF page: 169
9.4 study characteristics and correlation matrices 161
Table 9.35: Laukka, E. J., Lövdén, M., Herlitz, A., Karlsson, S., Ferencz, B.,Pantzar, A., ... & Bäckman, L. (2013). Genetic effects on old-agecognitive functioning: a population-based study. Psychology andAging, 28(1), 262. doi:10.1037/a0030829
N = 2694
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU LF SF
AGE 1 0.132 -0.347 -0.218 -0.452
SEX 0.132 1 -0.123 0.012 -0.016
EDU -0.347 -0.123 1 0.352 0.355
LF -0.218 0.012 0.352 1 0.498
SF -0.452 -0.016 0.355 0.498 1
Table 9.36: Lehrner, J., Moser, D., Klug, S., Gleiss, A., Auff, E., Pirker,W., & Pusswald, G. (2014). Subjective memory complaints,depressive symptoms and cognition in Parkinson’s diseasepatients. European Journal of Neurology, 21(10), 1276-1285.doi:10.1111/ene.12470
N = 247
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB LF SF COD BNT
AGE 1 0.016 -0.213 0.309 0.367 -0.128 -0.282 -0.427 -0.169
SEX 0.016 1 -0.117 0.148 0.128 -0.162 -0.27 -0.06 -0.036
EDU -0.213 -0.117 1 -0.177 -0.293 0.288 0.178 0.206 0.101
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 170PDF page: 170PDF page: 170PDF page: 170
162 appendices accompanying chapter 5
Table 9.37: Liebel, S. W., Jones, E. C., Oshri, A., Hallowell, E. S., Jerskey, B. A., Gunstad, J., & Sweet,L. H. (2017). Cognitive processing speed mediates the effects of cardiovascular disease onexecutive functioning. Neuropsychology, 31(1), 44-51. doi:10.1037/neu0000324
N = 73
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTB LF SF COD
AGE 1 0.006 -0.152 0.54 -0.15 -0.45 -0.447
SEX 0.006 1 -0.159 -0.068 0.278 0.158 0.141
EDU -0.152 -0.159 1 -0.198 0.029 0.193 0.179
TMTB 0.54 -0.068 -0.198 1 -0.366 -0.474 -0.627
LF -0.15 0.278 0.029 -0.366 1 0.618 0.324
SF -0.45 0.158 0.193 -0.474 0.618 1 0.465
COD -0.447 0.141 0.179 -0.627 0.324 0.465 1
Table 9.38: Llinàs-Reglà, J., Vilalta-Franch, J., López-Pousa, S., Calvó-Perxas, L., Torrents Rodas, D., &Garre-Olmo, J. (2017). The trail making test: Association with other neuropsychological mea-sures and normative values for adults aged 55 years and older From a Spanish-speakingpopulation-based sample. Assessment, 24(2), 183-196. doi:10.1177/1073191115602552
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 171PDF page: 171PDF page: 171PDF page: 171
9.4 study characteristics and correlation matrices 163
Table 9.39: Mohn, C., Lystad, J. U., Ueland, T., Falkum, E., & Rund, B. R.(2017). Factor analyzing the Norwegian MATRICS consensus cog-nitive battery. Psychiatry and Clinical Neurosciences, 71(5), 336-345.doi:10.1111/pcn.12513
N = 300
Sex coding: male > female
Education coding: higher is better
AGE SEX EDU TMTA SF COD VLT-TR
AGE 1 -0.007 0.262 0.329 0.089 -0.473 -0.289
SEX -0.007 1 -0.176 0.002 -0.104 -0.236 -0.166
EDU 0.262 -0.176 1 0.062 0.139 0.037 0.063
TMTA 0.329 0.002 0.062 1 -0.176 -0.503 -0.225
SF 0.089 -0.104 0.139 -0.176 1 0.191 0.25
COD -0.473 -0.236 0.037 -0.503 0.191 1 0.449
VLT-TR -0.289 -0.166 0.063 -0.225 0.25 0.449 1
Table 9.40: Morrens, M., Hulstijn, W., Matton, C., Madani, Y., VanBouwel, L., Peuskens, J., & Sabbe, B. G. C. (2008). Delin-eating psychomotor slowing from reduced processing speedin schizophrenia. Cognitive Neuropsychiatry, 13(6), 457-471.doi:10.1080/13546800802439312
N = 26
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU VLT-TR VLT-DR
AGE 1 0.182 -0.04 -0.04 0.17
SEX 0.182 1 0 -0.049 -0.024
EDU -0.04 0 1 -0.011 -0.237
VLT-TR -0.04 -0.049 -0.011 1 0.719
VLT-DR 0.17 -0.024 -0.237 0.719 1
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 172PDF page: 172PDF page: 172PDF page: 172
164 appendices accompanying chapter 5
Table 9.41: Ojeda, N., Pena, J., Schretlen, D. J., Sanchez, P., Aretouli, E., Elizagarate, E.,... & Gutierrez, M. (2012). Hierarchical structure of the cognitive processesin schizophrenia: the fundamental role of processing speed. Schizophrenia Re-search, 135(1), 72-78. doi:10.1016/j.schres.2011.12.004
N = 53
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA LMI LMII DSB COD
AGE 1 -0.172 -0.243 0.625 -0.04 -0.053 -0.441 -0.589
Table 9.42: de Paula, J. J., Bertola, L., Avila, R. T., Moreira, L., Coutinho, G., de Moraes, E.N., ... & Malloy-Diniz, L. F. (2013). Clinical applicability and cutoff values for anunstructured neuropsychological assessment protocol for older adults with lowformal education. PLoS One, 8(9), 1-9. doi:10.1371/journal.pone.0073167
N = 96
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU LF SF DSF DSB VLT-TR VLT-DR
AGE 1 -0.141 -0.163 0.016 -0.085 -0.111 -0.179 -0.153 -0.018
SEX -0.141 1 0.274 0.091 0.305 0.212 0.098 0.176 0.254
EDU -0.163 0.274 1 0.411 0.564 0.211 0.401 0.447 0.309
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 173PDF page: 173PDF page: 173PDF page: 173
9.4 study characteristics and correlation matrices 165
Table 9.43: Reppermund, S., Sachdev, P. S., Crawford, J., Kochan, N. A., Slavin, M.J., Kang, K., ... & Brodaty, H. (2011). The relationship of neuropsycho-logical function to instrumental activities of daily living in mild cogni-tive impairment. International Journal of Geriatric Psychiatry, 26(8), 843-852.doi:10.1002/gps.2612
N = 469
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB LMII LF SF BNT VLT-TR VLT-DR
Table 9.44: Ricarte, J. J., Ros, L., Latorre, J. M., Muñoz, M. D., Aguilar, M. J., &Hernandez, J. V. (2016). Role of anxiety and brooding in specificity ofautobiographical recall. Scandinavian Journal of Psychology, 57(6), 495-500.doi:10.1111/sjop.12323
N = 210
Sex coding: male > female
Education coding: higher is better
AGE SEX EDU LF SF
AGE 1 0.138 -0.886 -0.37 -0.545
SEX 0.138 1 0.011 0.089 0.01
EDU -0.886 0.011 1 0.291 0.436
LF -0.37 0.089 0.291 1 0.669
SF -0.545 0.01 0.436 0.669 1
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 174PDF page: 174PDF page: 174PDF page: 174
166 appendices accompanying chapter 5
Table 9.45: Royall, D. R., Bishnoi, R. J., & Palmer, R. F. (2015).Serum IGF-BP2 strongly moderates age’s effect on cognition:a MIMIC analysis. Neurobiology of Aging, 36(7), 2232-2240.doi:10.1016/j.neurobiolaging.2015.04.003
N = 875
Sex coding: female > male
Education coding: higher is better
Table 9.46: Schmidt, C. S., Schumacher, L. V., Römer, P., Leonhart, R.,Beume, L., Martin, M., ... & Kaller, C. P. (2017). Are seman-tic and phonological fluency based on the same or distinctsets of cognitive processes? Insights from factor analyses inhealthy adults and stroke patients. Neuropsychologia, 99, 148-155.doi:10.1016/j.neuropsychologia.2017.02.019
N = 69
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU LF SF
AGE 1 -0.001 0.855 0.003 0.25
SEX -0.001 1 -0.041 0.194 0.133
EDU 0.855 -0.041 1 -0.032 0.189
LF 0.003 0.194 -0.032 1 0.521
SF 0.25 0.133 0.189 0.521 1
Table 9.47: Siedlecki, K. L., Manly, J. J., Brickman, A. M., Schupf, N., Tang, M.X., & Stern, Y. (2010). Do neuropsychological tests have the samemeaning in Spanish speakers as they do in English speakers?.Neuropsychology, 24(3), 402-411. doi:10.1037/a0017515
N = 2113
Sex coding: female > male
Education coding: higher is better
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 175PDF page: 175PDF page: 175PDF page: 175
9.4 study characteristics and correlation matrices 167
Table 9.48: Snitz, B. E., Yu, L., Crane, P. K., Chang, C. C. H., Hughes,T. F., & Ganguli, M. (2012). Subjective cognitive complaints ofolder adults at the population level: an item response theoryanalysis. Alzheimer disease and associated disorders, 26(4), 344-351.doi:10.1097/WAD.0b013e3182420bdf
Table 9.49: Tractenberg, R. E., Fillenbaum, G., Aisen, P. S., Liebke, D. E., Yu-moto, F., & Kuchibhatla, M. N. (2010). What the CERAD batterycan tell us about executive function as a higher-order cognitivefaculty. Current Gerontology and Geriatrics Research, 510614, 1-10.doi:10.1155/2010/510614
N = 918
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU SF BNT VLT-TR VLT-DR
AGE 1 -0.042 -0.428 -0.425 -0.509 -0.546 -0.533
SEX -0.042 1 0.037 -0.024 -0.072 0.211 0.169
EDU -0.428 0.037 1 0.518 0.584 0.567 0.496
SF -0.425 -0.024 0.518 1 0.546 0.559 0.524
BNT -0.509 -0.072 0.584 0.546 1 0.6 0.53
VLT-TR -0.546 0.211 0.567 0.559 0.6 1 0.801
VLT-DR -0.533 0.169 0.496 0.524 0.53 0.801 1
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 176PDF page: 176PDF page: 176PDF page: 176
168 appendices accompanying chapter 5
Table 9.50: Tse, C. S., Balota, D. A., Yap, M. J., Duchek, J. M., & McCabe, D. P. (2010). Effects of healthyaging and early stage dementia of the Alzheimer’s type on components of response timedistributions in three attention tasks. Neuropsychology, 24(3), 300-315. doi:10.1037/a0018274
Table 9.51: Tuokko, H. A., Chou, P. H. B., Bowden, S. C., Simard, M., Ska, B., & Crossley, M. (2009).Partial measurement equivalence of French and English versions of the Canadian Study ofHealth and Aging neuropsychological battery. Journal of the International NeuropsychologicalSociety, 15(3), 416-425. doi:10.1017/S1355617709090602
N = 786
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU LF SF COD VLT-TR
AGE 1 0.07 0.06 -0.02 -0.16 -0.28 -0.3
SEX 0.07 1 0.05 0.15 -0.06 0.07 0.25
EDU 0.06 0.05 1 0.51 0.33 0.51 0.3
LF -0.02 0.15 0.51 1 0.48 0.58 0.42
SF -0.16 -0.06 0.33 0.48 1 0.51 0.37
COD -0.28 0.07 0.51 0.58 0.51 1 0.52
VLT-TR -0.3 0.25 0.3 0.42 0.37 0.52 1
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 177PDF page: 177PDF page: 177PDF page: 177
9.4 study characteristics and correlation matrices 169
Table 9.52: Valenzuela, M. J., & Sachdev, P. (2007). Assessment of complex mental activity acrossthe lifespan: development of the Lifetime of Experiences Questionnaire (LEQ). Psy-chological Medicine, 37(7), 1015-1025. doi:10.1017/S003329170600938X
N = 73
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU TMTA TMTB LMI LMII LF SF DSF DSB COD BNT
Table 9.53: Waldinger, R. J., Cohen, S., Schulz, M. S., & Crowell, J. A. (2015). Security of attachmentto spouses in late life: Concurrent and prospective links with cognitive and emotionalwell-being. Clinical Psychological Science, 3(4), 516-529. doi:10.1177/2167702614541261
517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-Agelink517531-L-bw-AgelinkProcessed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018Processed on: 26-2-2018 PDF page: 178PDF page: 178PDF page: 178PDF page: 178
170 appendices accompanying chapter 5
Table 9.54: Watts, A. S., Loskutova, N., Burns, J. M., & Johnson, D. K. (2013).Metabolic syndrome and cognitive decline in early Alzheimer’sdisease and healthy older adults. Journal of Alzheimer’s Dis-ease, 35(2), 253-265. doi:10.3233/JAD-121168
N = 73
Sex coding: male > female
Education coding: higher is better
AGE SEX EDU LMI LMII
AGE 1 -0.051 -0.072 -0.264 -0.296
SEX -0.051 1 0.284 -0.138 -0.165
EDU -0.072 0.284 1 0.153 0.081
LMI -0.264 -0.138 0.153 1 0.847
LMII -0.296 -0.165 0.081 0.847 1
Table 9.55: Wettstein, M., Kuzma, E., Wahl, H. W., & Heyl, V. (2016). Cross-sectional and longitudinal relationship between neuroticism andcognitive ability in advanced old age: The moderating role ofsevere sensory impairment. Aging & Mental Health, 20(9), 918-929.doi:10.1080/13607863.2015.1049119
N = 150
Sex coding: female > male
Education coding: higher is better
AGE SEX EDU SF DSB
AGE 1 0.077 0.124 -0.19 -0.061
SEX 0.077 1 -0.009 0.007 0.132
EDU 0.124 -0.009 1 0.262 0.124
SF -0.19 0.007 0.262 1 0.198
DSB -0.061 0.132 0.124 0.198 1
Table 9.56: Williams, P. G., Suchy, Y., & Kraybill, M. L. (2010). Five-factor model personality traits and executive functioning amongolder adults. Journal of Research in Personality, 44(4), 485-491.doi:10.1016/j.jrp.2010.06.002